code: def forward(self, data):
      x = bk_feat(data)
      for layer in range(self.layer_number):
          op = getattr(self, f"op_{layer}")
          x = bk_gconv(op, data, x)
          if layer != self.layer_number - 1:
              x = F.leaky_relu(x)
              x = F.dropout(x, p=self.dropout, training=self.training)
      return F.log_softmax(x, dim=1)
  
file_path: AutoGL/autogl/module/nas/space/single_path.py
imports: from autogl.module.nas.space.operation import gnn_map
  import typing
  import torch
  import torch.nn.functional
  from .None import register_nas_space
  from .base import apply_fixed_architecture
  from .base import BaseSpace
  from ...model import BaseAutoModel
  from ....utils import get_logger
  from ...model import AutoGCN
  from ..backend import *
  from ..utils import count_parameters, measure_latency
label_desc: Use image node_id 3 for calling the SinglePathNodeClassificationSpace obj's underlying member method code with example usage: obj.forward(data) and returns: F